The field of technology is conventional and spectral, iterative CT reconstruction using the so-called separable paraboloid surrogate, SPS, method with ordered subsets of projection data. This method does a Newton-like update while approximating the Hessian matrix of the cost function with a diagonal matrix. The inverse of this diagonal matrix is called “denominator”.
The separable paraboloid surrogate, SPS, method is in iterative reconstruction for CT usually combined with ordered-subsets, i.e. for one image update only a subset of the data is used. This heuristic increases the convergence speed at the cost of a slightly inexact solution. The subsets are usually designed in a way that a small number of equally distributed projections is taken from the full dataset for the calculation of the gradient applied in the Newton-like update.